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Driving a racing car requires a tremendous amount of skill. Now, artificial intelligence has challenged the idea that this skill is exclusive to humans - and it might even change the way automated vehicles are designed.
A modern Formula 1 race is a breathtaking display of engineering precision. Yet the popularity of the sport arguably has less to do with the performance of the cars than with the skill and daring displayed by the drivers as they push those cars to the limit. Success on the race track has been a celebrated human achievement for more than a century. Will it now become a similar triumph for artificial intelligence (AI)? On page 223, Wurman et al.1 take a step in this direction by introducing Gran Turismo (GT) Sophy, a neural-network driver capable of outperforming the best human players of the video game Gran Turismo.
The objective in racing is easily defined: if you complete the circuit in less time than your competitors, you win. However, achieving this goal involves a complicated battle with physics, because negotiating the track requires careful use of the frictional force between the tyre and the road, and this force is limited. Using some of that friction for braking, for instance, leaves less force available for rounding a corner.
More specifically, each tyre can produce a frictional force proportional to the vertical force, or load, that connects it to the road. As the car accelerates, the load shifts to the rear tyres, leaving less frictional force for the front tyres. This can induce understeer, in which the steering wheel cannot generate more cornering force and effectively becomes a hand rest as thecar ploughs out of the turn. By contrast, when the car brakes, the load shifts to the front of the car. This can lead to over steer, meaning that the rear...